Creation of an algorithm for clinical decision support for treatment of opioid use disorder with buprenorphine in primary care

• Main Authors: Adriane M. dela Cruz, Robrina Walker, Ronny Pipes, Sidarth Wakhlu, Madhukar H. Trivedi
• Format: Article
• Language: English
• Published: BMC 2021-02-01
• Series: Addiction Science & Clinical Practice
• Subjects: Measurement based care; Buprenorphine; Clinical decision support
• Online Access: https://doi.org/10.1186/s13722-021-00222-0

Abstract Background The treatment capacity for opioid use disorder (OUD) lags far behind the number of patients in need of treatment. Capacity is limited, in part, by the limited number of physicians who offer office based OUD treatment with buprenorphine. Measurement based care (MBC) has been proposed as a means to support primary care physicians in treating OUD. Here, we propose a set of measures and a clinical decision support algorithm to provide MBC for the treatment of OUD. Methods We utilized literature search and expert consensus to identify measures for universal screening and symptom tracking. We used expert consensus to create the clinical decision support algorithm. Results The Tobacco, Alcohol, Prescription medication, and other Substance use (TAPS) tool was selected as the best published measure for universal screening in primary care. No published measure was identified as appropriate for symptom tracking or medication adherence; therefore, we created the OUD Symptom Checklist from the DSM-5 criteria for OUD and the Patient Adherence Questionnaire for Opioid Use Disorder Treatment (PAQ-OUD) to assess medication adherence. We developed and present a clinical decision support algorithm to provide direct guidance regarding treatment interventions during the first 12 weeks of buprenorphine treatment. Conclusion Creation of these tools is the necessary first step for implementation of MBC for the treatment of OUD with buprenorphine in primary care. Further work is needed to test the feasibility and acceptability of these tools. Trial Registration ClinicalTrials.gov; NCT04059016; 16 August 2019; retrospectively registered; https://clinicaltrials.gov/ct2/show/NCT04059016